Parameter Identification and Application of Reinforced Concrete Column Based on Modified Ibarra-Medina-Krawinkler Hysteretic Model

被引：0
作者：
Guo Y. [1 ,2 ]
Long M. [1 ]
机构：
[1] College of Civil Engineering, Hunan University, Changsha
[2] Key Laboratory of Building Safety and Energy Efficiency, Hunan University, Ministry of Education, Changsha
来源：
Hunan Daxue Xuebao/Journal of Hunan University Natural Sciences | 2021年 / 48卷 / 01期
基金：
中国国家自然科学基金;
关键词：
Hysteretic behavior; Hysteretic model; Parameter identification; Particle swarm optimization algorithm; Robust SVD-UKF algorithm;
D O I：
10.16339/j.cnki.hdxbzkb.2021.01.014
中图分类号：
学科分类号：
摘要：
A method for identifying the backbone curve parameters of the modified Ibarra-Medina-Krawinkler (IMK) model by using quasi-static test data of reinforced concrete columns and thus improving the simulation accuracy of reinforced concrete frame structures is proposed in this paper. In this method, a robust unscented Kalman filtering algorithm based on singular value decomposition(robust SVD-UKF algorithm) is introduced to suppress the influence of gross error of the observation on the parameter identification, and the particle swarm optimization algorithm is adopted to automatically optimize the initial covariance matrix, the process and measurement noise matrices. The identification of backbone curve parameters of the modified IMK model is realized using MATLAB, in which the symmetric and asymmetric hysteresis behavior of the columns in the positive and negative direction is considered. The effectiveness of the proposed method is verified by model backbone curve parameter identification based on the measured hysteretic curves of reinforced concrete columns and its application in the nonlinear simulation of frame structures. © 2021, Editorial Department of Journal of Hunan University. All right reserved.
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页码：126 / 134
页数：8
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